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Table 7 Relative bias in the three-component mixture model

From: Segmentation and intensity estimation for microarray images with saturated pixels

Parameter

GMM0

CGMM

GMM1

 

10

40

70

10

40

70

10

40

70

Ï€1 = 0.7

0.0011

0.0010

0.0011

0.0011

0.0011

0.0012

0.0006

-0.0002

-0.0088

μ1 = 2, 000

0.0015

0.0015

0.0015

0.0015

0.0015

0.0015

0.0015

0.0014

0.0033

σ1 = 1, 000

-0.0044

-0.0045

-0.0045

-0.0044

-0.0045

-0.0044

-0.0051

-0.0077

-0.0117

Ï€2 = 0.1

-0.0022

-0.0017

-0.0023

-0.0032

-0.0032

-0.0046

0.0176

0.1637

0.5294

μ2 = 15, 000

0.0008

0.0005

0.0004

0.0003

-0.0001

0.0003

0.0117

0.1679

0.7195

σ2 = 6, 000

-0.0262

-0.0249

-0.0255

-0.0276

-0.0271

-0.0285

0.0100

0.3923

1.8881

μ 3

-0.0001

0.0000

-0.0002

-0.0002

0.0002

-0.0010

-0.0053

-0.0384

-0.1352

σ 3

-0.0071

-0.0076

-0.0071

-0.0049

-0.0028

-0.0033

-0.1161

-0.4601

-0.9294

  1. Simulation with true K = 3: Relative bias based on runs with K correctly selected by BIC. The models considered were regular Gaussian mixture for complete, uncensored data (GMM0), censored Gaussian mixture for censored data, and regular Gaussian mixture for censored data (GMM1). Percents of saturated foreground pixels were set at 10% (μ3 = 52, 700, σ3 = 10, 000), 40% (μ3 = 62, 500, σ3 = 12, 000) and 70% (μ3 = 75, 000, σ3 = 18, 000).